Difficult intubation assessment using statistical factor analysis decision tree

Hsien Chang Wang, Wei Hao Chen, Chia Chi Tseng, Yu Hsien Chiu

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Correct and rapid tracheal intubation is an essential anesthesia task for surgical operations. Intubation highly depends on the subjective judgment and experience of the anesthetist. This paper proposes a statistical factor analysis approach to model the preferences of expert anesthetists to enable more accurate pre-operation judgments in cases of difficult intubation. Factor analysis combined with the mutual information between factors is used to generate a robust decision tree (DT) using Bartletts node splitting criterion for better decision-making. A tablet computer application is also developed to assist judgment. Several experiments were performed to investigate judgment accuracy and learning effects. Our proposed approach outperformed both a well-known C5.0 DT and an expert opinion derived DT. Encouraging results concerning robustness and efficiency were observed for our approach.

Original languageEnglish
Pages (from-to)710-721
Number of pages12
JournalJournal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A
Issue number6
Publication statusPublished - 2014 Aug 18

All Science Journal Classification (ASJC) codes

  • General Engineering


Dive into the research topics of 'Difficult intubation assessment using statistical factor analysis decision tree'. Together they form a unique fingerprint.

Cite this